School of Energy and Environment, Southeast University, Nanjing, China.
Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China.
Indoor Air. 2022 Jun;32(6):e13056. doi: 10.1111/ina.13056.
Since the outbreak of COVID-19 in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has spread worldwide. This study summarized the transmission mechanisms of COVID-19 and their main influencing factors, such as airflow patterns, air temperature, relative humidity, and social distancing. The transmission characteristics in existing cases are providing more and more evidence that SARS CoV-2 can be transmitted through the air. This investigation reviewed probabilistic and deterministic research methods, such as the Wells-Riley equation, the dose-response model, the Monte-Carlo model, computational fluid dynamics (CFD) with the Eulerian method, CFD with the Lagrangian method, and the experimental approach, that have been used for studying the airborne transmission mechanism. The Wells-Riley equation and dose-response model are typically used for the assessment of the average infection risk. Only in combination with the Eulerian method or the Lagrangian method can these two methods obtain the spatial distribution of airborne particles' concentration and infection risk. In contrast with the Eulerian and Lagrangian methods, the Monte-Carlo model is suitable for studying the infection risk when the behavior of individuals is highly random. Although researchers tend to use numerical methods to study the airborne transmission mechanism of COVID-19, an experimental approach could often provide stronger evidence to prove the possibility of airborne transmission than a simple numerical model. All in all, the reviewed methods are helpful in the study of the airborne transmission mechanism of COVID-19 and epidemic prevention and control.
自 2019 年 12 月 COVID-19 爆发以来，严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）已在全球范围内传播。本研究总结了 COVID-19 的传播机制及其主要影响因素，如气流模式、空气温度、相对湿度和社交距离。现有病例的传播特征提供了越来越多的证据表明，SARS-CoV-2 可以通过空气传播。本调查回顾了概率和确定性研究方法，如威尔斯-赖利方程、剂量反应模型、蒙特卡罗模型、欧拉方法的计算流体动力学（CFD）、拉格朗日方法的 CFD 和实验方法，这些方法用于研究空气传播机制。威尔斯-赖利方程和剂量反应模型通常用于评估平均感染风险。只有与欧拉方法或拉格朗日方法相结合，这两种方法才能获得空气传播颗粒浓度和感染风险的空间分布。与欧拉方法和拉格朗日方法相比，蒙特卡罗模型更适合研究个体行为高度随机时的感染风险。尽管研究人员倾向于使用数值方法来研究 COVID-19 的空气传播机制，但实验方法通常可以提供比简单数值模型更强有力的证据来证明空气传播的可能性。总之，所回顾的方法有助于研究 COVID-19 的空气传播机制和疫情防控。
